CrawlBot AI vs. Kustomer AI
Kustomer AI focuses on CRM-native support and agent workflows. CrawlBot is built for grounded website answers with citations, freshness controls, and strong embed security. Here is how they differ and how to combine them.
Comparison
| Dimension | CrawlBot AI | Kustomer AI |
|---|---|---|
| Grounding | Hybrid RAG with citations and refusal policy | CRM data, macros, and flows |
| Freshness | Sitemap-first crawl, IndexNow, incremental recrawl | Updates tied to CRM data and content syncs |
| Analytics | Per-embed impressions, opens, chats, messages, fallback reasons | Conversation and agent metrics |
| Security | SRI, strict widget CSP, origin checks, SSO, formal threat model | CRM platform security; embed controls vary |
| Multi-tenant | Agency friendly styling and quotas per tenant | Single brand focus |
When CrawlBot is the better fit
- Visitors want instant, cited answers on marketing, docs, or policy pages.
- Agencies manage multiple brands and need isolated styling, quotas, and analytics.
- Security teams demand strict CSP and origin validation for embeds.
- Ops teams want retrieval transparency and adaptive thresholds to curb hallucinations quickly.
When to rely on Kustomer
- Deep CRM workflows, case management, and agent collaboration drive support.
- Authenticated interactions require customer context that lives in Kustomer.
- Teams already tuned macros and flows inside Kustomer.
Running both
- Deploy CrawlBot on public pages for grounded answers and citations.
- Keep Kustomer for account or ticket flows requiring CRM data.
- Use triggers to hand off account intents from CrawlBot to Kustomer agents.
- Track containment, CSAT, and outdated feedback to adjust CrawlBot crawl cadence and thresholds.
Grounded answers cut bounce on the open web while Kustomer remains the system of record for customer conversations.